* Update relative `ROOT` logic

* python 3.9 Path().is_relative_to() removal

* Allow YOLOv5 execution from arbitrary `cwd`

* Fix str bugs

* Automatic Chinese fonts plotting

* Default PIL=False

`check_file()` is now limited to searching opt-in directories: /data, /models, /utils. This prevents large non-project directories like /.git and /venv from being searched, which may cause `check_file()` to slow significantly.

* Validate best.pt on train end

* 0.7 iou for COCO only

* pass callbacks

* active model.float() if not half

* print Validating best.pt...

* add newline

Add badge with link to join the new YOLOv5 Slack Forum!
https://join.slack.com/t/ultralytics/shared_invite/zt-w29ei8bp-jczz7QYUmDtgo6r6KcMIAg

* Fix `root` referenced before assignment

Fix for bug introduced by #4919 discovered on VOC autodownload:
```
python train.py --data VOC.yaml
```

* Cleanup

* Replace `os.system('unzip file.zip')` -> `ZipFile.extractall()`

* Cleanup

* Add arguments to TensorFlow NMS call

* Add regex substitution to reorder Identity_*

* Delete reorder in docstring

* Cleanup

* Cleanup2

* Removed `+ \` on string ends (not needed)
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Avoid out-of-image class labels

* Update plots.py

* Cleanup
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* evolve fix

* Enable login timeout

* fix pkg

* check rank

* don't relogin

* fix

* reformat

* evolve fix

* Enable login timeout

* fix pkg

* check rank

* don't relogin

* Annotator `check_font()` RANK -1 remove progress

* Cleanup

* Simplify `check_requirements()` usage

* remove assert, print()

* Update `sys.path.append(str(ROOT))`

* Cleanup

* Refactor argparser printing to `print_args()`

* Cleanup

* evolve fix

* Enable login timeout

* fix pkg

Defines dataset labels *.cache version in a single place, fixing a bug introduced in #4845.

PR should produce datasets sorted alphabetically by filename. Cache version incremented to 0.5. 

Note: will force a one-time re-caching of existing datasets on first-use.

* Unpin Pillow

* Update requirements.txt

* Update plots.py

* Fix val.py study plot

* call plot_val_study

* Rename plot_study_txt to plot_val_study

* Add fused conv support

* Set all saved_model values to non trainable

* Fix TFLite fp16 model export

* Fix int8 TFLite conversion

Follows #4823

* added callbacks

* added back callback to main

* added save_dir to callback output

* merged in upstream

* removed ghost code

* added url check

* Add url2file()

* Update file-only
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

Also disable `/weights` dir creation when evolving as no weights are saved and empty folder causes user expectations of weights.

* Add `--int8` argument

* parents[0] bug fix

* Fix order

Thank you for sharing nice open-source codes 👍

I applied to shuffle the order of all 4(or 9) images in mosaic augmentation

Currently, the order of images in mosaic augmentation is not completely random.
The remaining images except the first are randomly arranged. Apply shuffle all to increase the diversity of data composition.